setNaiveBayes

<p>The number of variables selected by feature selection prior to training the model (this is required due to Naive Bayes requring a non sparse matrix)</p>

variableNumber

<p>Create setting for naive bayes model with python</p>

A package for creating patient level prediction models. Given a
cohort of interest and an outcome of interest, the package can use data in the
OMOP Common Data Model to build a large set of features. These features can then
be assessed to fit a predictive model using a number of machine learning algorithms.
Several performance measures are implemented for model evaluation.

Jenna Reps

PatientLevelPrediction

Package for patient level prediction using data in the OMOP Common Data
Model

Martijn Schuemie

Marc Suchard

Patrick Ryan

Peter Rijnbeek

setNaiveBayes function

Create setting for naive bayes model with python — setNaiveBayes

Create setting for naive bayes model with python

setNaiveBayes: Create setting for naive bayes model with python

Description

Usage

Arguments

Examples